Consensus of sampled-data multi-agent networking systems via model predictive control

This paper presents a theoretical framework to design and analyze the consensus of a sampled-data multi-agent networking system via model predictive control (MPC). We introduce a distributed MPC weighted-average consensus protocol for a continuous-time multi-agent network in the sampled-data setting, and prove such a sampled-data multi-agent system asymptotically reaches the weighted-average consensus via the distributed MPC protocol with both fixed and switching network topologies. Numerical examples verify the effectiveness of the distributed MPC consensus protocol, which is beneficial to the convergence of consensus and the feasible range of the sampling interval.